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At least 613 records · Page 34

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

Nonlinear gyrokinetic predictions of SPARC burning plasma profiles enabled by surrogate modeling

Multi-channel, nonlinear predictions of core temperature and density profiles are performed for the SPARC tokamak accounting for both kinetic neoclassical and fully nonlinear gyro-kinetic turbulent fluxes. A series of flux-tube, nonlinear, electromagnetic simulations using the CGYRO code with six gyrokinetic species are coupled to a nonlinear optimizer using Gaussian process regression techniques. The simultaneous evolution of energy sources, including alpha heat, radiation, and energy exchange, coupled with these high fidelity models and techniques, leads to a converged solution in electron temperature, ion temperature and electron density channels with a minimal number of expensive gyrokinetic simulations without compromising accuracy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics

Flow depth and velocity are the most important hydrodynamic variables that govern various river functions, including water resources, navigation, sediment transport, and biogeochemical cycling. Existing high-resolution flow depth simulations rely on either computationally expensive river hydrodynamic models (RHMs) or data-driven models with formidable training costs, whereas data-driven modeling of flow velocity has rarely been explored. Here, using the hybrid Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) model, we developed a downscaling approach to construct high-resolution flow depth and velocity from a two-dimensional (2-D) RHM simulation at coarse resolution. The LSG models were trained and tested in an urban watershed in Houston using two different hurricane-driven flood events. The high-resolution (as fine as 30 m resolution) and low-resolution (mostly 1000 m resolution) meshes include 664 724 and 14 536 grid cells, respectively. The results showed that through downscaling, the simulation errors were reduced to less than one-fourth and one-third of the errors of the low-resolution 2-D RHM for flow depth and velocity, respectively. Our analysis further revealed that the dominant uncertainty sources of the downscaled hydrodynamics are different, with flow velocity dominated by the dimensionality reduction error, which we reduced by using a regionalized training procedure. The downscaling approach achieves an 84-fold acceleration in computational time compared to the high-resolution 2-D RHM, making high-fidelity ensemble flood modeling feasible. More importantly, the developed method provides an opportunity to couple large-scale hydrodynamical processes with local physical, chemical, and biological processes in river models.

Tan, Zeli [Pacific Northwest National Laboratory (↗

Impacts of the Addition of Sodium Reactor Experiment (SRE) and DR-3 Fuel from H-Canyon to Tank 40 on Acid Stoichiometry and Hydrogen Production

H-Canyon plans to discard Sodium Reactor Experiment (SRE) material that is currently stored in Tanks 16.3 and 16.4. Savannah River Remediation (SRR) determined that a portion of the SRE material can be added to Sludge Batch 9 (SB9) in Tank 40 and the remainder will be added to Sludge Batch 10 (SB10) that is currently being prepared in Tank 51. A processing flowsheet for both the nitric-formic acid flowsheet and the nitric-glycolic acid flowsheet were previously developed for SB9 sludge-only and coupled operation with the Actinide Removal Process – Modular Caustic Side Solvent Extraction Unit (ARP-MCU) and the Salt Waste Processing Facility (SWPF). Due to the compositional change in Tank 40 after the addition of SRE material, it is necessary to determine the influence on the acid stoichiometry operating window and hydrogen production for SB9 processing. An assessment was completed to address the influence of an addition of SRE and DR-3 Fuel from H-Canyon on the chemistry of Tank 40, the defined acid stoichiometry window (with and without SWPF streams) for the nitric-formic and nitric-glycolic acid flowsheets, and the resulting influence of the hydrogen production. Hydrogen production during the SRAT/SME cycles consists of thermolytic, radiolytic, and catalytic hydrogen. For the nitric-formic acid flowsheet, catalytic hydrogen dominates the hydrogen production during DWPF operation mode for the SRAT and SME vessels. This report was written to summarize that assessment. No SRNL testing is needed prior to adding up to 7,100 additional gallons of SRE and DR-3 Fuel from H-Canyon to Tank 40. Also, the addition of SRE will not exceed the Shielded Cells reported values for catalytic hydrogen for either the nitric-formic acid flowsheet (Technical Safety Requirement (TSR) limit of 0.15 lb/h) or the nitric-glycolic acid flowsheet (TSR limit 0.024 lb/h). The addition of the ARP stream from SWPF and the use of the nitric-glycolic acid flowsheet are both expected to decrease hydrogen generation, leading to a larger safety margin in the CPC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Modeling of thermal pressurization in tight claystone using sequential THM coupling: Benchmarking and validation against in-situ heating experiments in COx claystone

We apply thermoporoelasticity and a sequentially coupling technique for modeling thermally-driven coupled Thermo-Hydro-Mechanical (THM) processes in tight claystone. A THM benchmark case with a corresponding analytic solution for thermoporoelasticity under a constant heat loading verifies the model. Thereafter, two in situ heating experiments are simulated for model validation: a smaller-scale heating experiment (TED experiment) and a larger-scale experiment (ALC experiment) in Callovo-Oxfordian (COx) claystone at the Meuse/Haute-Marne underground research laboratory in France. The model exhibits good performance to match the observed temperature and pore pressure evolution for the smaller-scale TED experiment. For the larger-scale ALC experiment, general trends of thermal-pressurization are captured in the modeling, but pressure is underestimated at some monitoring points during cool-down. This indicates that the THM response in the field may be affected by the variability of rock's properties or irreversible or time-dependent mechanical processes that are not included in the current thermoporoelastic model. The main contributions of this work are as follows: (1) we verify and validate the numerical simulator, TOUGH-FLAC, to be a valuable coupled THM modeling tool; (2) prove that the laboratory determined material parameters can be used as reference values for upscaling experiments. However, to better identify and quantify THM processes with modeling of in situ tests, more emphasize should be dedicated to obtaining high-quality mechanical deformation data.

58 GEOSCIENCES↗

Toroidal modeling of runaway avalanche in DIII-D discharges

Abstract A toroidal modeling tool is developed to study the runaway electron (RE) avalanche production process in tokamak plasmas, by coupling the Rosenbluth–Putvinski avalanche model (Rosenbluth and Putvinski 1997 Nucl. Fusion 37 1355) with an n = 0 magneto-hydrodynamic (MHD) solver. Initial value numerical simulations are carried out for two DIII-D discharges with different plasma shapes (one near circular, and the other with high elongation). It is found that, assuming the same level of about 1% seed current level, the Rosenbluth–Putvinski model somewhat underestimates the RE plateau current for the circular-shaped plasma, as compared with that measured in DIII-D experiments. For an elongated, higher current plasma, simulations find strong runaway current avalanche production despite the lack of measured plateau RE current in experiments. A possible reason for this discrepancy is a lack of additional RE dissipation physics in the present two-dimensional model. Systematic scans of the plasma boundary shape, at fixed pre-disruption plasma current, find that the plasma elongation helps to reduce the RE avalanche production, confirming recent results obtained with an analytic model (Fülöp et al 2020 J. Plasma Phys. 86 474860101). The effect of the plasma triangularity (either positive or negative), on the other hand, has a minor effect. On the physics side, the avalanche process involves two competing mechanisms associated with the electric field. On the one hand, a stronger electric field produces a higher instantaneous avalanche growth rate. On the other hand, a fast growing RE current quickly reduces the fraction of the conduction current together with the electric field, and hence a faster dissipation of the poloidal flux. As a final result of these two dynamic processes, the runaway plateau current is not always the largest with the strongest initial electric field. These results lay the foundation for future self-consistent inclusion of the MHD dynamics and the RE amplification process.

Physics↗

A Review of Lattice-Boltzmann Models Coupled with Geochemical Modeling Applied for Simulation of Advanced Waterflooding and Enhanced Oil Recovery Processes

To maintain economic profit and improve the oil production efficiency after the primary and secondary production phase, advanced waterflooding techniques such as low salinity waterflooding in carbonate reservoirs have been investigated in numerical simulations, laboratory experiments, and field pilot tests. Multiple underlying mechanisms have been proposed based on these studies, and they are still under debate. Various numerical modeling approaches are introduced, but there exists a lack of a pore-scale comprehensive modeling scheme to fully understand the processes. Lattice-Boltzmann method (LBM) is a type of numerical fluid flow modeling technique that shows capabilities and flexibilities in modeling pore-scale fluid flow to integrate physical–chemical processes within complex structures. The intrinsic feature of LBM makes it a promising framework for simulating advanced waterflooding due to its flexibility, accuracy, and parallel efficiency. LBM works either by itself for solving reactive transport problems or by coupling with a third-party reaction solver. This review mainly introduces the LBM fluid flow and reactive transport capabilities and the concept and modeling approaches to simulate advanced waterflooding techniques. Meanwhile, an evaluation of the coupled LBM models for enhanced oil recovery (EOR) simulations is discussed with future research challenges and directions concluded.

02 PETROLEUM↗

Nonadiabatic Derivative Couplings through Multiple Franck–Condon Modes Dictate the Energy Gap Law for Near and Short-Wave Infrared Dye Molecules

Near infrared (NIR, 700–1000 nm) and short-wave infrared (SWIR, 1000–2000 nm) dye molecules exhibit significant nonradiative decay rates from the first singlet excited state to the ground state. While these trends can be empirically explained by a simple energy gap law, detailed mechanisms of nearly universal behavior have remained unsettled for many cases. Theoretical and experimental results for two representative NIR/SWIR dye molecules reported here clarify the key mechanism for the observed energy gap law behavior. It is shown that the first derivative nonadiabatic coupling terms serve as major coupling pathways for nonadiabatic decay processes from the first excited singlet state to the ground state for these NIR and SWIR dye molecules and that vibrational modes other than the highest frequency modes also make significant contributions to the rate. Finally, this assessment is corroborated by further theoretical comparison with possible alternative mechanisms of intersystem crossing to triplet states and also by comparison with experimental data for deuterated molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid dissolution without elemental fractionation by laser driven hydrothermal processing

Traditional dissolution of geologic samples often requires a significant time investment. Here, we present an alternative method for the dissolution of geologic materials using laser-driven hydrothermal processing (LDHP). LDHP uses laser energy directed onto a submerged sample, which increases the temperature and pressure at the liquid–sample interface and drives the hydrothermal dissolution coupled with photomechanical spallation, an ablative process. This uses focused 527 nm laser energy at 40 W average power, 1 kHz pulse repetition rate, and 115 ns pulse duration. Importantly, when LDHP is performed on basalt geostandards (BCR-2 and BHVO-2) using the conditions outlined, we show that LDHP does not produce significant elemental fractionation and, thus, can be considered an alternative processing method to traditional mechanical crushing and acid digestion. Additionally, it is possible using LDHP to utilize the spatially confined beam to target and selectively isolate individual phases in a rock, potentially alleviating the need for mechanical separation of inclusions that are difficult to physically isolate. Furthermore, using this outlined method of LDHP, we demonstrate full dissolution of 120 mg of obsidian in 85 minu, meaning that LDHP is a potentially very useful method when sample processing is time sensitive.

58 GEOSCIENCES↗

Ultrafast CMOS image sensors and data-enabled super-resolution for multimodal radiographic imaging and tomography

We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus $super$-$resolution$). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Understanding Microstructure Variability in Vapor-Deposited Energetic Materials by Using Phase-Field Methods

Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.

36 MATERIALS SCIENCE↗

Ultrafast CMOS image sensors and data-enabled super-resolution for multimodal radiographic imaging and tomography

We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus ‘super-resolution’). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.

47 OTHER INSTRUMENTATION↗

Optimization of leaf morphology in relation to leaf water status: A theory

The leaf economic traits such as leaf area, maximum carbon assimilation rate, and venation are all correlated and related to water availability. Furthermore, leaves are often broad and large in humid areas and narrower in arid/semiarid and hot and cold areas. We use optimization theory to explain these patterns. We have created a constrained optimization leaf model linking leaf shape to vein structure that is integrated into coupled transpiration and carbon assimilation processes. The model maximizes net leaf carbon gain (NPPleaf) over the loss of xylem water potential. Modeled relations between leaf traits are consistent with empirically observed patterns. As the results of the leaf shape-venation relation, our model further predicts that a broadleaf has overall higher NPPleaf compared to a narrowleaf. In addition, a broadleaf has a lower stomatal resistance compared to a narrowleaf under the same level of constraint. With the same leaf area, a broadleaf will have, on average, larger conduits and lower total leaf xylem resistance and thus be more efficient in water transportation but less resistant to cavitation. By linking venation structure to leaf shape and using water potential as the constraint, our model provides a physical explanation for the general pattern of the covariance of leaf traits through the safety-efficiency trade-off of leaf hydraulic design.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring an ‘ideal hill': how lithology and transport mechanisms affect the possibility of a steady state during weathering and erosion

We introduce a model of chemical reaction within hills to explore how evolving porosity (and by inference, permeability) affects flow pathways and weathering. The model consists of hydrologic and reactive-transport equations that describe alteration of ferrous minerals and feldspar. These reactions were chosen because previous work emphasized that oxygen- and acid-driven weathering affects porosity differently in felsic and mafic rocks. A parameter controlling the order of the fronts is presented. In the absence of erosion, the two reaction fronts move at different velocities and the relative depths depend on geochemical conditions and starting composition. In turn, the fronts and associated changes in porosity drastically affect both the vertical and lateral velocities of water flow. For these instances, estimates of weathering advance rates based on simple models that posit unidirectional constant-velocity advection do not apply. In the model hills, weathering advance rates diminish with time as the Darcy velocities decrease with depth. The system can thus attain a dynamical steady state at any erosion rate where the regolith thickness is constant in time and velocities of both fronts become equal to one another and to the erosion rate. The slower the advection velocities in a system, the faster it attains a steady state. For example, a massive rock with relatively fast-dissolving minerals such as diabase -- where solute transport across the reaction front mainly occurs by diffusion -- can reach a steady state more quickly than granitoid rocks in which advection contributes to solute transport. The attainment of a steady state is controlled by coupling between weathering and hydrologic processes that force water to flow horizontally above reaction fronts where permeability changes rapidly with depth and acts as a partial barrier to fluid flow.

54 ENVIRONMENTAL SCIENCES↗

PtCoO 2 for Scaled Interconnects

Copper (Cu) interconnects are an increasingly important bottleneck in integrated circuits due to energy consumption and latency caused by the notable increase in Cu resistivity as dimensions decrease, primarily due to electron scattering at surfaces. Herein, the potential of a directional conductor, PtCoO 2 , which has a low bulk resistivity and a distinctive anisotropic structure that mitigates electron surface scattering is showcased. Thin films of PtCoO 2 of various thicknesses are synthesized by molecular beam epitaxy (MBE) coupled with a postdeposition annealing process and the superior quality of PtCoO 2 films is demonstrated by multiple characterization techniques. The thickness‐dependent resistivity curve illustrates that PtCoO 2 significantly outperforms effective Cu (Cu with TaN barriers) and Ru in resistivity below 20.0 nm with a more than 6x reduction compared to effective Cu below 6.0 nm, having a value of only 6.32 μΩ cm at 3.3 nm. It is determined that grain boundary scattering can still be improved for even lower resistivities in this material system through a combination of experiments and theoretical simulations. PtCoO 2 is therefore a highly promising alternative material for future interconnect technologies promising lower resistivities, better stability, and significant improvements in energy efficiency and latency for advanced integrated circuits.

Li, Yansong [Department of Electrical Engineering ↗

Towards gradient multimaterial toolpath generation for direct ink writing with connected fermat spirals

This work describes advances towards a reproducible, parametrically defined algorithm for generating graded multimaterial toolpaths for direct ink writing. Expanding on the existing Fermat space-filling algorithm and coupling with image-driven processing techniques, we demonstrate the fabrication of multimaterial structures. Here, material composition is encoded within toolpaths by parsing hue values from a multi-colored image. By performing dynamic velocity compensation based on local curvature and Euclidean distance filtering, internal voids are mitigated while optimizing print fidelity. Here, the work opens new avenues for designing complex toolpaths with locally programmable composition.

3D Printing↗

Activity gradient mass transport accelerated corrosion of stainless steel in molten salt

Advanced energy systems based on molten salt technologies have gained increasing interest, and their design and construction are likely going to involve the use of materials of dissimilar chemistries. With dissimilar materials being used, galvanic coupling induced corrosion acceleration is one of the mechanisms believed to be an issue for the deployment of molten salt systems. However, non-galvanic interaction mechanisms such as activity gradient mass transport have also been theorized to represent a potential challenge. Unfortunately, the two effects have often been compounded in the literature, such that it is still unclear which degradation mechanisms are at play in these systems. In the following study, electrochemical measurements are used to predict the effect that galvanic coupling would have on dissimilar materials submerged in the same molten salt medium. Dissimilar material salt exposure tests are then performed to investigate whether galvanic coupling or activity gradient driven processes account for the levels of materials degradation observed. Finally, these separate effect electrochemical and corrosion experiments uniquely elucidate the degradation mechanisms in dissimilar materials systems.

36 MATERIALS SCIENCE↗